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| train_score = [] | |
| test_score = [] | |
| k_vals = [] | |
| for k in range(1, 21): | |
| k_vals.append(k) | |
| knn = KNeighborsClassifier(n_neighbors = k) | |
| knn.fit(X_train, y_train) | |
| tr_score = knn.score(X_train, y_train) | |
| train_score.append(tr_score) | |
| te_score = knn.score(X_test, y_test) | |
| test_score.append(te_score) |
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